code: def SKIP_test_ragged_input_with_padding(self):
      input_data = get_input_dataset(
          tf.ragged.constant([[[1, 2, 3, 4, 5]], [[2], [3]]])
      )
      expected_output = np.array(
          [
              [
                  [1.0, 2.0, 3.0, 4.0, 5.0],
                  [-1.0, -1.0, -1.0, -1.0, -1.0],
              ],
              [
                  [2.0, -1.0, -1.0, -1.0, -1.0],
                  [3.0, -1.0, -1.0, -1.0, -1.0],
              ],
          ]
      )
  
      layers = [ToDense(pad_value=-1), Final()]
      model = get_model_from_layers(
          layers,
          input_shape=(None, None),
          input_ragged=True,
          input_dtype=tf.dtypes.int32,
      )
      model.compile(optimizer="sgd", loss="mse", metrics=["accuracy"])
      output = model.predict(input_data)
      self.assertAllEqual(output, expected_output)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow.python.framework import test_util
  from tensorflow_text.python.keras.layers.todense import ToDense
label_desc: Use image node_id 2 for calling the RaggedTensorsToDenseLayerTest obj's underlying member method code with example usage: obj.SKIP_test_ragged_input_with_padding() without return types